Technical Field
The present invention relates to a question answering technology and, more particularly, to a question answering technology to generate answers by information searches among hybrid languages.
Description of the Related Art
Nowadays, a computer system has been improved by its language applicability and most computer systems may be operated under a multi-lingual environment. In such a computer system, a question answering system is widely known and the conventional question answering system could generate answers in the same language as a question language. In addition, an information source for generating the answer was that accumulating information provided in the same language as the question language. Hereafter, the language of the information source is referred to simply as an IS language. Such conventional question and answer systems (hereafter simply referred to a QA system), such as a simple background technology, have been described in following literatures:
(1) Neumann, Günter, and Bogdan Sacaleanu. “Experiments on robust NL question interpretation and multi-layered document annotation for a cross-language question/answering system.” Multilingual Information Access for Text, Speech and Images. Springer Berlin Heidelberg, 2005. Pages 411-422. (http://research.nii.ac.jp/˜ntcadm/workshop/OnlineProceedings5/data/CLQA/NTCIR5-CLQA-IsozakiH.pdf);
(2) Isozaki, Hideki, Katsuhito Sudoh, and Hajime Tsukada. “NTT's Japanese-English cross-language question answering system.” Proc. of NTCIR-5 Meeting. 2005 (http://research.nii.ac.jp/˜ntcadm/workshop/OnlineProceedings5/data/CLQA/NTCIR5-CLQA-IsozakiH.pdf);
(3) Stolcke, Andreas, et al. “Dialogue act modeling for automatic tagging and recognition of conversational speech.” Computational linguistics 26.3 (2000): 339-373 (http://arxiv.org/pdf/cs/0006023.pdf) and
(4) International Patent Publication WO2011/088053A2.
The conventional QA system usually searches contents using queries in the question language while targeting the information source provided in the IS language, which is the same language as that of the question. However, Japanese Wikipedia contains more information about Japanese temples than English Wikipedia even though the question has been issued in English. Additionally, English Wikipedia contains more information about American movies than does Japanese Wikipedia even though the question has been issued in Japanese.
When an English speaker inputs a question about Japanese temples in an English language, a mono-lingual QA system can handle this question by searching the information source provided in English but not the information source provided in Japanese; nevertheless Japanese information source may contain and provide much more contents expected proper for an answer of the question.
In turn, when a Japanese speaker wants to issue a question about an American movie, a mono-lingual Japanese QA system accepts this question in Japanese. However, the language of information sources to be searched has been restricted to that provided in Japanese. Nevertheless, English information sources may contain more documents related to the American movie. In the conventional environments described above, the QA system may have difficulty in finding more right and/or relevant answers from the information source provided in the different language from the question language.